Terrence J. Sejnowski

Research

Terrence J. Sejnowski, professor and head of the Computational Neurobiology Laboratory, is a pioneer in the field of computational neuroscience.

Among other things, Sejnowski is interested in the hippocampus, believed to play a major role in learning and memory; and the cerebral cortex, which holds our knowledge of the world and how to interact with it. In his lab, Sejnowski's team uses sophisticated electrical and chemical monitoring techniques to measure changes that occur in the connections among nerve cells in the hippocampus during a simple form of learning. They use the results of these studies to instruct large-scale computers to mimic how these nerve cells work. By studying how the resulting computer simulations can perform operations that resemble the activities of the hippocampus, Sejnowski hopes to gain new knowledge of how the human brain is capable of learning and storing memories. This knowledge ultimately may provide medical specialists with critical clues to combating Alzheimer's disease and other disorders that rob people of the critical ability to remember faces, names, places and events.

"My goal is to discover the principles linking brain mechanisms and behavior. My laboratory uses
both experimental and modeling techniques to study the biophysical properties of neurons and
synapses, the sites at which neurons connect with each other, as well as the population dynamics of
large networks of neurons."

Multiple sclerosis affects an estimated
400,000 Americans and more than 2.5
million people worldwide. A chronic, often
disabling disease that attacks the central
nervous system, it is characterized by a
baffling range of neurological symptoms,
including numbness, tingling, motor weakness,
paralysis and vision loss. It is thought
to result when the immune system attacks
the myelin sheath that insulates axons, the
nerve fibers that conduct electrical impulses
to and from the brain and between neurons
within the brain. Ordinarily, the myelin
speeds up the signals the axons transmit,
but when axons lose their insulation, either
signal conduction fails because the demyelinated
axons are unable to generate an
impulse, or the axons become hyperexcitable
and overcompensate by firing even in the
absence of an input.

The first computer model of axonal transmission,
developed in the 1950s for the giant
axon of the squid, which lacks myelin,
tracked positively charged sodium and potassium
ions, whose movements across the
neuronal membrane generate the necessary
electrical signals. Building on that model,
Sejnowski and his team included myelin in
their own model, then demyelinated one of
the sections and incorporated all the changes
known to take place as a result. Most prior
studies had focused on the sodium channel
because it is responsible for initiating the
electrical signal. But to everyone's surprise,
Sejnowski's group found that it was the ratio
of densities between the sodium channel and
a previously ignored but ubiquitous voltageinsensitive
potassium current, called the leak
current, that determines whether neurons
can fire properly.

If the sodium level drops, an accompanying
drop in the leak current will maintain the
signal, whereas if the sodium drops but
the leak current doesn't, signal transmission
may fail. Conversely, if the sodium level is
too high and the leak current doesn't increase,
a patient may experience twitching.
Sejnowski's model not only offers an explanation
for many of the bizarre symptoms that
multiple sclerosis patients experience but
could also provide a new target for drugs
that increase or decrease the potassium leak
current to maintain a constant ratio and
offer relief.